arXiv AI
Jul 24
VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method
arXiv:2607. 21400v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions.
SatNav: A Scalable Benchmark for Long-Horizon UAV Vision-Language Navigation from Satellite Imagery
SatNav is a new, scalable benchmark for long‑horizon vision‑language navigation (VLN) with unmanned aerial vehicles (UAVs), built from high‑resolution satellite imagery. It generates 118,000 navigation episodes across 59 scenes in 18 cities, using satellite crops to approximate UAV nadir views and featuring three task families—Boundary, Landmark, and Route—to test long‑term memory and geospatial reasoning. The benchmark also introduces SwiftVLN, a modular framework for memory component experimentation, and demonstrates that models trained on satellite data can transfer to real‑flight UAV observations.
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arXiv AI
Jun 19
See-and-Reach: Precise Vision-Language Navigation for UAVs within the Field of View
arXiv:2606. 20045v1 Announce Type: cross Abstract: UAV Vision-Language Navigation (UAV-VLN) is typically formulated as a holistic search-and-reach problem, where long-range target discovery and final target approach are optimized and evaluated jointly.
arXiv AI
Jul 10
FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation
arXiv:2607. 08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs.
arXiv AI
Jul 22
Fly0: Persistent Metric Anchoring for Zero-Shot Aerial Vision-Language Navigation
arXiv:2602. 15875v2 Announce Type: replace-cross Abstract: Current Visual-Language Navigation (VLN) methodologies face a trade-off between semantic understanding and control precision.
Hugging Face Trending Papers
Jun 18
See-and-Reach: Precise Vision-Language Navigation for UAVs within the Field of View
UAV Vision-Language Navigation (UAV-VLN) is typically formulated as a holistic search-and-reach problem, where long-range target discovery and final target approach are optimized and evaluated jointly. This formulation makes it difficult to assess a critical capability of aerial embodied agents, namely whether a UAV can accurately ground a visible target and translate vision-language evidence into precise 3D motion once the target enters its field of view.
arXiv AI
Sep 10
AirAnchor: Bridging Local and Global Spatial Information for Zero-Shot Aerial Vision-and-Language Navigation
arXiv:2609.08442v1 Announce Type: cross Abstract: Aerial Vision-and-Language Navigation requires drones to follow natural-language instructions and navigate through complex urban environments. Accura...
arXiv AI
Jun 6
WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
arXiv:2606. 06147v1 Announce Type: new Abstract: End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation.
Hugging Face Trending Papers
Jul 9
FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation
Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs. Compared with GPS-dependent or pre-programmed navigation, VLN supports intuitive human-machine interaction and stronger environmental adaptability, requiring tight integration of high-level semantic reasoning and low-latency flight control.
arXiv AI
Jun 29
SpatialUAV: Benchmarking Spatial Intelligence for Low-Altitude UAV Perception, Collaboration, and Motion
arXiv:2606. 27876v1 Announce Type: cross Abstract: Spatial intelligence is essential for low-altitude unmanned aerial vehicle (UAV) perception, collaboration, and navigation.
arXiv AI
Aug 13
DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation
arXiv:2608. 12308v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it has reached a navigation goal under partial observability.
arXiv AI
3d ago
NavGen: Visual Generative Models as a Scalable Data Engine for Embodied 3D Navigation
NavGen introduces a text-to-video data generation pipeline that creates about 400K vision‑language navigation episodes for both indoor and outdoor scenes, using high‑fidelity visual generative models. The approach includes a style‑diversification method to scale up rare, hard‑to‑collect data. Models trained on NavGen data outperform those trained on existing UAV navigation datasets and achieve a 75% success rate in real‑world flying experiments.
arXiv AI
1d ago
AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search
AerialDojo-200K is a large-scale benchmark suite for open-world aerial object-goal search, featuring 42 simulation scenes across four families and 21 types, including urban, natural, infrastructure, and disaster environments. The dataset contains 205,732 task instances—over 100K semantic-goal and over 100K image-goal tasks—each with a collision-free reference trajectory and multi-view video recordings. A unified evaluation framework splits scenes into 21 in-distribution and 21 out-of-distribution sets, and preliminary tests on multimodal large language models show significant room for improvement in general-purpose aerial agents.